Jiaming Ji

Hello! I’m a first-year PhD student at the Institute of Artificial Intelligence, Peking University, advised by Prof. Yaodong Yang (both a good teacher and a helpful friend in my life). In 2024, I was honored to receive the first batch of National Natural Science Foundation funding for the Youth Student Basic Research Project (Ph.D. students); the sole recipient from Peking University in the field of intelligence, and I am also a recipient of the Peking University President’s Scholarship. Before this, I conducted research on safe reinforcement learning and won the championship in the NeurIPS 2022 MyoChallenge for robotic dexterous manipulation. Currently, my core research interest lies in AI Safety and Alignment, particularly focusing on the safety and value alignment of large models:

• Safety Alignment of Large Language Models: Given the biases and discriminations that may exist in pre-training data, LLMs may exhibit unintended behaviors. I am interested in alignment methods (e.g., Reinforcement Learning from human feedback (RLHF)) and post-hoc alignment methods to ensure the safety and trustworthy of LLMs.

• Theoretical Explanations and Mechanism Design for Alignment: Aligning these AI System (e.g. LLMs) effectively to ensure consistency with human intentions and values (though some views may question universal values) is a significant current challenge. I am particularly interested in ensuring the feasibility of these alignment methods in both theoretical and practical mechanisms.

• Large Models and Cross-Domain Applications (LM + X): I am interested in the application of large models in various domain, such as healthcare and education, and the potential impact of rapid industry development and iteration brought about by large models.